Video clips generation system

ABSTRACT

A method for generating a preview associated with a media file is provided. The method may include receiving a plurality of social comments associated with a plurality of frames corresponding to the media file. The method may also include storing the received plurality of social comments in a repository, whereby the received plurality of social comments is stored with a frame marker. The method may further include analyzing the stored plurality of social comments. The method may additionally include classifying the analyzed plurality of social comments according to at least one sentiment and at least one keyword in the media file.

BACKGROUND

The present invention relates generally to the field of computers, andmore particularly to media.

A large number of videos and films are available on content providers.As such, it may be challenging for a person to select from the vastvariety of choices in a short period of time. Therefore, many peopleoften rely on social indicators, such as suggestions and advice offriends to assist in the selection of a video, film, movie, ortelevision show. However, the social indicators may not be preciseenough to ensure that the video, film, movie, or television show is agood choice for that particular person since such social indicatorsoften do not take into account individual tastes.

SUMMARY

According to one embodiment, a method for generating a previewassociated with a media file is provided. The method may includereceiving a plurality of social comments associated with a plurality offrames corresponding to the media file. The method may also includestoring the received plurality of social comments in a repository,whereby the received plurality of social comments is stored with a framemarker. The method may further include analyzing the stored plurality ofsocial comments. The method may additionally include classifying theanalyzed plurality of social comments according to at least onesentiment and at least one keyword in the media file.

According to another embodiment, a computer system for generating apreview associated with a media file is provided. The computer systemmay include one or more processors, one or more computer-readablememories, one or more computer-readable tangible storage devices, andprogram instructions stored on at least one of the one or more storagedevices for execution by at least one of the one or more processors viaat least one of the one or more memories, whereby the computer system iscapable of performing a method. The method may include receiving aplurality of social comments associated with a plurality of framescorresponding to the media file. The method may also include storing thereceived plurality of social comments in a repository, whereby thereceived plurality of social comments is stored with a frame marker. Themethod may further include analyzing the stored plurality of socialcomments. The method may additionally include classifying the analyzedplurality of social comments according to at least one sentiment and atleast one keyword in the media file.

According to yet another embodiment, a computer program product forgenerating a preview associated with a media file is provided. Thecomputer program product may include one or more computer-readablestorage devices and program instructions stored on at least one of theone or more tangible storage devices, the program instructionsexecutable by a processor. The computer program product may includeprogram instructions to receive a plurality of social commentsassociated with a plurality of frames corresponding to the media file.The computer program product may also include program instructions tostore the received plurality of social comments in a repository, wherebythe received plurality of social comments is stored with a frame marker.The computer program product may further include program instructions toanalyze the stored plurality of social comments. The computer programproduct may additionally include program instructions to classify theanalyzed plurality of social comments according to at least onesentiment and at least one keyword in the media file.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

These and other objects, features and advantages of the presentinvention will become apparent from the following detailed descriptionof illustrative embodiments thereof, which is to be read in connectionwith the accompanying drawings. The various features of the drawings arenot to scale as the illustrations are for clarity in facilitating oneskilled in the art in understanding the invention in conjunction withthe detailed description. In the drawings:

FIG. 1 illustrates a networked computer environment according to atleast one embodiment;

FIG. 2 illustrates an exemplary system architecture according to atleast one embodiment;

FIGS. 3A-3B are operational flowcharts illustrating the steps carriedout by a program to generate video clips according to at least oneembodiment;

FIG. 4 is a block diagram of internal and external components ofcomputers and servers depicted in FIG. 1 according to at least oneembodiment;

FIG. 5 is a block diagram of an illustrative cloud computing environmentincluding the computer system depicted in FIG. 1, according to at leastone embodiment; and

FIG. 6 is a block diagram of functional layers of the illustrative cloudcomputing environment of FIG. 5, according to at least one embodiment.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. This invention may, however, be embodied inmany different forms and should not be construed as limited to theexemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the scope of this invention to thoseskilled in the art. In the description, details of well-known featuresand techniques may be omitted to avoid unnecessarily obscuring thepresented embodiments.

Embodiments of the present invention relate generally to the field ofcomputers, and more particularly to a media file, such as, but notlimited to videos, films, movies, and television/network/cable shows.The following described exemplary embodiments provide a system, methodand program product to, among other things, provide a video clipgeneration system. Therefore, the present embodiment has the capacity toimprove the technical field of media by automatically generating apreview from semantic analysis of user comments on the frames of a mediafile (i.e., movies, videos, films, and television/network/cable shows).As such, the present embodiment may create a better preview for a mediafile, such as a movie. More specifically, the present embodiment mayinclude a module that collects social comments about frames of a movie(i.e., media file) and stores them with a frame-marker and a module thatanalyzes the comments and classifies them according to sentiment andrecognized keywords in the movie domain. Furthermore, the presentembodiment may include a module that optionally takes a user inputtedsearch string and collects the frames that have tagged comments thathave positive sentiment and match the criteria of the search string (ifpresent); collects a set of frames directly before and after the matchedframes, to create a set of snippets from the movie; appends the snippetstogether into a preview; and a module to present the preview to theuser. However, a user may also request to view a preview withoutentering a search string, whereby the preview is generated fromappending a set of snippets including a collection of frames that areassociated with the requested media file. Additionally, the preview canbe generated from a plurality of media resources.

As previously described, a large number of videos and films areavailable on content providers. As such, it may be challenging for aperson to select from the vast variety of choices in a short period oftime. Currently, video clips or trailers are used as an advertisingmethod to attract viewers. However, the video clips and trailers aretypically pre-prepared by the film company. Therefore, these video clipsand trailers may not always highlight the most popular aspects of themovie. Furthermore, since the video clips and trailers are preparedbefore the movie is available, they are often prepared without inputfrom real viewers. Additionally, video reviews and comments may be usedas a way to present information about the movie from real viewers,however, the reviews and comments may be limited to words and staticpictures. As such, it may be advantageous, among other things, toautomatically generate a preview from semantic analysis of user commentson the frames of the movie.

According to at least one implementation, the present embodiment mayallow a user to submit comments about a frame of the movie or televisionseries, by using a secondary device, such as a tablet or laptopconnected to the service streaming the film or TV show series, orthrough a pause menu on the viewing device itself. The presentembodiment may also contain a module that performs semantic analysis ofthe user entered comments on each frame to determine which framesinvoked a positive emotional response such as excitement or enjoyment,or contained certain objects or actors/actresses. For example, if a userwants to watch a 3 minute movie that only contains a certain actor oractress, the user may input the duration as 3 minutes, and input theactor's or actress' name as keywords. Then, the present embodiment canoutput the customized clips.

More specifically, the present embodiment may connect input fromdifferent users via the internet (or a graphical user interface, anonline communication system, or a use of social media) and may satisfy alarge number of media (including, but not limited to movies, shows,videos, etc.). Also, the present embodiment may allow the user to searchmovies based on the social comments made on parts of the movies inaddition to allowing the user a mechanism to provide their own inputinto what they are interested in.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The following described exemplary embodiments provide a system, methodand program product for generating video clips. According to at leastone implementation, the present embodiment may provide interactiveactivities between users by generating video clips that are irrespectiveof the movie itself. As such, a user may utilize the generated videoclips to find videos more quickly based on the user's interests.

Referring to FIG. 1, an exemplary networked computer environment 100 inaccordance with one embodiment is depicted. The networked computerenvironment 100 may include a computer 102, a processor 104, and a datastorage device 106 that is enabled to run a software program 108 and aVideo Clips Generation Program 116A. The networked computer environment100 may also include a server 114 that is enabled to run a Video ClipsGeneration Program 116B and that may interact with a database 112A, 112Band a communication network 110. The networked computer environment 100may include a plurality of computers 102 and servers 114, only one ofwhich is shown. The communication network may include various types ofcommunication networks, such as a wide area network (WAN), local areanetwork (LAN), a telecommunication network, a wireless network, a publicswitched network and/or a satellite network. It should be appreciatedthat FIG. 1 provides only an illustration of one implementation and doesnot imply any limitations with regard to the environments in whichdifferent embodiments may be implemented. Many modifications to thedepicted environments may be made based on design and implementationrequirements.

The client computer 102 may communicate with the Video Clips GenerationProgram 116B running on server computer 114 via the communicationsnetwork 110. The communications network 110 may include connections,such as wire, wireless communication links, or fiber optic cables. Aswill be discussed with reference to FIG. 4, server computer 114 mayinclude internal components 800 a and external components 900 a,respectively, and client computer 102 may include internal components800 b and external components 900 b, respectively. Server computer 114may also operate in a cloud computing service model, such as Software asa Service (SaaS), Platform as a Service (PaaS), or Infrastructure as aService (IaaS). Server 114 may also be located in a cloud computingdeployment model, such as a private cloud, community cloud, publiccloud, or hybrid cloud. Client computer 102 may be, for example, amobile device, a telephone, a personal digital assistant, a netbook, alaptop computer, a tablet computer, a desktop computer, or any type ofcomputing devices capable of running a program, accessing a network, andaccessing a database 112A, 112B. According to various implementations ofthe present embodiment, the Video Clips Generation Program 116A, 116Bmay interact with a database 112A, 112B that may be embedded in variousstorage devices, such as, but not limited to a computer 102, a networkedserver 114, or a cloud storage service.

As previously described, the client computer 102 may access the VideoClips Generation Program 116B, running on server computer 114 via thecommunications network 110. For example the Video Clips GenerationProgram 116A, 116B running on a client computer 102 and server computer114 may allow a user to submit comments about a frame of the movie ortelevision series, by using a secondary device 102, such as a tablet orlaptop connected to the service streaming the film or TV show series, orthrough a pause menu on the viewing device 102 itself. The presentembodiment may also contain a module (which will be explained in furtherdetail in FIG. 2) that performs semantic analysis of the user enteredcomments on each frame to determine which frames invoked a positiveemotional response, such as excitement or enjoyment, or containedcertain objects or a specific actor or actress. The Video ClipsGeneration method is explained in more detail below with respect toFIGS. 2-3B.

Referring now to FIG. 2, an exemplary system architecture 200 inaccordance with one embodiment is depicted. According to at least oneimplementation, the present embodiment may include a data source 202,such as two databases 112A, 112B. One database 112A is for the movie,with frame markers. The other database 112B may be utilized as a storageof social media comments, tagged against the movie and the frame marker.

The present embodiment may also include a semantic analysis component204 which is based on existing technology. As such, a semantic module204 using existing mechanisms for semantic analysis may annotate eachuser comment with sentiment. Additionally, the semantic module mayrecognize movie related keywords, such as an actor's name or a locationof a movie set.

Next, a processor 206, may collect the annotated information and filterthe appropriate frame markers, given the desired sentiment and/orrecognized keywords. Then, the output 208A-208C combines the frames intoa final preview which is presented to the user 210A-210C.

Referring now to FIGS. 3A-3B, operational flowcharts 300 illustratingthe steps carried out by a program that generates video clips inaccordance with one embodiment are depicted. According to at least oneimplementation, the present embodiment may dynamically create a previewfor a given video based on a search string. The preview may be createdby consuming a set of social comments on the individual frames on avideo, and piecing together the closest matching scenes whose socialcomments matched the search string. As such, a dynamically created andhighly targeted preview for a video is provided to a user, which mayimprove the ability for a customer to decide if the video is a videothat the person would want to watch or not.

With respect to FIG. 3A at 302, social comments (i.e., social mediacomments) are received about frames of a movie. For example, a user maysubmit comments about a frame of a movie or television series, by usinga secondary device 102 (FIG. 1), such as a tablet or laptop connected tothe service streaming the film or the TV show series. However, in analternate implementation, the user may enter such comments through apause menu (i.e., GUI) on the viewing device itself.

Then at 304, the user entered social comments are stored (along with aframe marker) in a repository, such as a database 112B (FIG. 1). Aspreviously described, the present embodiment may include the use of twodatabases 112A, 112B (FIG. 1). One database 112A (FIG. 1) is for themovie, with frame markers. The other database 112B (FIG. 1) may beutilized as a storage of social media comments, tagged against the movieand the frame marker.

Next at 306, the stored comments are analyzed. According to at least oneimplementation, a module 204 (FIG. 2) may perform semantic analysis(using existing technology) of the user entered comments on each frameto determine which frames invoked a positive emotional response such asexcitement or enjoyment, or contained certain objects, location of sets,actors, or actresses.

Then at 308, the analyzed stored comments are classified according tosentiment and recognized keywords in the movie domain. As previouslyexplained, a semantic analysis module may annotate each user commentwith sentiment.

Optionally, the present embodiment may utilize a user inputted searchstring (entered via a graphical user interface, for example) todynamically create a preview for a given video based on the enteredsearch string. Therefore, with respect to FIG. 3B at 310, a searchstring regarding a video preference is received. For example, if a userwants to watch a 3 minute movie that only contains a certain actor oractress, the user may input the duration as 3 minutes, and input theactor's or actress' name as keywords.

Then at 312, the frames that have tagged comments which have a positivesentiment and match the criteria of the entered search string arecollected (if present). As previously described, a processor 206 (FIG.2) may collect the annotated information and filter the appropriateframe markers, given the desired sentiment and/or recognized keywords.

Next at 314, a set of frames directly before and after the matchedframes are collected and then at 316, a set of snippets (based on thecollected set of frames from step 314) are created. Next at 318, thecreated set of snippets ae appended together (i.e., the collected framesare combined together) into a preview and then at 320 the preview ispresented to the user. As such, the preview is created based on the userdefined search terms and social metadata attached to the video.

It may be appreciated that FIGS. 2 and 3A-3B provide only anillustration of one implementation and do not imply any limitations withregard to how different embodiments may be implemented. Manymodifications to the depicted environments may be made based on designand implementation requirements. As previously mentioned, the presentembodiment may optionally utilize a user inputted search string todynamically create a preview for a given video based on the enteredsearch string.

As such, by generating the preview dynamically through semantic analysisthe preview would have benefits over a pre-provided preview. Forexample, by allowing the user to enter what they are interested in, thepreview can be tailored to their interests, which may have a higherprobability of capturing their interest in that particular movie. Assuch, this may increase viewership of the movies and shows provided bythe service and may increases customer satisfaction. Additionally, byusing the present embodiment, even without user entry of interests, thesystem can generate a preview of the scenes that were the best receivedby existing viewers, leading to a higher quality preview. Furthermore,the preview generation can be combined with existing search capabilitiesenhancing the results that are returned from the search.

The present embodiment automatically creates a preview from a videobased on a user's search string and makes use of social commentsassociated to the frames of the video, to extract the relevant contentand generate the preview. As such, the present embodiment generates thepreview clip from social comments provided on the video source frames,and is able to generate the preview from parts of the video whose socialcomments relate to the search. As a result, the present embodiment mayprovide for a richer search capability based on how others haveinterpreted the content of the video. More specifically, the preview iscreated based on the user defined search terms and social metadataattached to the video in order to recognize relevant content in thevideo.

FIG. 4 is a block diagram 400 of internal and external components ofcomputers depicted in FIG. 1 in accordance with an illustrativeembodiment of the present invention. It should be appreciated that FIG.4 provides only an illustration of one implementation and does not implyany limitations with regard to the environments in which differentembodiments may be implemented. Many modifications to the depictedenvironments may be made based on design and implementationrequirements.

Data processing system 800, 900 is representative of any electronicdevice capable of executing machine-readable program instructions. Dataprocessing system 800, 900 may be representative of a smart phone, acomputer system, PDA, or other electronic devices. Examples of computingsystems, environments, and/or configurations that may be represented bydata processing system 800, 900 include, but are not limited to,personal computer systems, server computer systems, thin clients, thickclients, hand-held or laptop devices, multiprocessor systems,microprocessor-based systems, network PCs, minicomputer systems, anddistributed cloud computing environments that include any of the abovesystems or devices.

User client computer 102 (FIG. 1) and network server 114 (FIG. 1) mayinclude respective sets of internal components 800 a,b and externalcomponents 900 a,b illustrated in FIG. 4. Each of the sets of internalcomponents 800 include one or more processors 820, one or morecomputer-readable RAMs 822 and one or more computer-readable ROMs 824 onone or more buses 826, and one or more operating systems 828 and one ormore computer-readable tangible storage devices 830. The one or moreoperating systems 828 and the Software Program 108 (FIG. 1) and theVideo Clips Generation Program 116A (FIG. 1) in client computer 102(FIG. 1) and the Video Clips Generation Program 116B (FIG. 1) in networkserver 114 (FIG. 1) are stored on one or more of the respectivecomputer-readable tangible storage devices 830 for execution by one ormore of the respective processors 820 via one or more of the respectiveRAMs 822 (which typically include cache memory). In the embodimentillustrated in FIG. 4, each of the computer-readable tangible storagedevices 830 is a magnetic disk storage device of an internal hard drive.Alternatively, each of the computer-readable tangible storage devices830 is a semiconductor storage device such as ROM 824, EPROM, flashmemory or any other computer-readable tangible storage device that canstore a computer program and digital information.

Each set of internal components 800 a,b also includes a R/W drive orinterface 832 to read from and write to one or more portablecomputer-readable tangible storage devices 936 such as a CD-ROM, DVD,memory stick, magnetic tape, magnetic disk, optical disk orsemiconductor storage device. A software program, such as the SoftwareProgram 108 (FIG. 1) and the Video Clips Generation Program 116A, 116B(FIG. 1) can be stored on one or more of the respective portablecomputer-readable tangible storage devices 936, read via the respectiveR/W drive or interface 832 and loaded into the respective hard drive830.

Each set of internal components 800 a,b also includes network adaptersor interfaces 836 such as a TCP/IP adapter cards, wireless Wi-Fiinterface cards, or 3G or 4G wireless interface cards or other wired orwireless communication links. The Software Program 108 (FIG. 1) and theVideo Clips Generation Program 116A (FIG. 1) in client computer 102(FIG. 1) and the Video Clips Generation Program 116B (FIG. 1) in networkserver 114 (FIG. 1) can be downloaded to client computer 102 (FIG. 1)and network server 114 (FIG. 1) from an external computer via a network(for example, the Internet, a local area network or other, wide areanetwork) and respective network adapters or interfaces 836. From thenetwork adapters or interfaces 836, the Software Program 108 (FIG. 1)and the Video Clips Generation Program 116A (FIG. 1) in client computer102 (FIG. 1) and the Video Clips Generation Program 116B (FIG. 1) innetwork server 114 (FIG. 1) are loaded into the respective hard drive830. The network may comprise copper wires, optical fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers.

Each of the sets of external components 900 a,b can include a computerdisplay monitor 920, a keyboard 930, and a computer mouse 934. Externalcomponents 900 a,b can also include touch screens, virtual keyboards,touch pads, pointing devices, and other human interface devices. Each ofthe sets of internal components 800 a,b also includes device drivers 840to interface to computer display monitor 920, keyboard 930 and computermouse 934. The device drivers 840, R/W drive or interface 832 andnetwork adapter or interface 836 comprise hardware and software (storedin storage device 830 and/or ROM 824).

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 5, illustrative cloud computing environment 500 isdepicted. As shown, cloud computing environment 500 comprises one ormore cloud computing nodes 100 with which local computing devices usedby cloud consumers, such as, for example, personal digital assistant(PDA) or cellular telephone 500A, desktop computer 500B, laptop computer500C, and/or automobile computer system 500N may communicate. Nodes 100may communicate with one another. They may be grouped (not shown)physically or virtually, in one or more networks, such as Private,Community, Public, or Hybrid clouds as described hereinabove, or acombination thereof. This allows cloud computing environment 500 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 500A-Nshown in FIG. 5 are intended to be illustrative only and that computingnodes 100 and cloud computing environment 500 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring now to FIG. 6, a set of functional abstraction layers 600provided by cloud computing environment 500 (FIG. 5) is shown. It shouldbe understood in advance that the components, layers, and functionsshown in FIG. 6 are intended to be illustrative only and embodiments ofthe invention are not limited thereto. As depicted, the following layersand corresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and video clips generation 96. A Video ClipsGeneration Program 116A, 116B (FIG. 1) may provide a video clipgeneration system which may improve the technical field of media byautomatically generating a preview from semantic analysis of usercomments on the frames of the movie (i.e., videos, films, andtelevision/network/cable shows).

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A processor-implemented method for generating apreview associated with a media file, the method comprising: receiving,by a processor, a plurality of social comments associated with aplurality of frames corresponding to the media file, wherein thereceived plurality of social comments comprises collecting a pluralityof input from a plurality of different users, wherein the plurality ofinput is obtained live via an internet, a graphical user interface, anonline communication system, or a use of social media via a secondarydevice connected to a service streaming the media file; storing thestreaming media file in a first repository with a plurality of framemarkers corresponding to the stored streaming media file; storing thereceived plurality of social comments in a second repository, analyzingthe stored plurality of social comments; annotating each social commentwithin the analyzed plurality of social comments with at least onesentiment and at least one keyword in the media file; classifying theanalyzed annotated plurality of social comments according to the atleast one sentiment and the at least one keyword in the media file,wherein classifying the annotated plurality of social comments comprisesdetermining a plurality of positive sentiments about a plurality offrames associated with the media file; receiving a search stringregarding a media file preference, wherein the search string is inputtedonline by a user; in response to receiving the search string regardingthe media file preference, determining from the first repository and thesecond repository a first plurality of frames that match a criteriaassociated with the received search string; determining a secondplurality of frames that include a set of frames directly before and aset of frames directly after the determined first plurality of framesthat match the criteria associated with the search string; creating aset of snippets based on the determined first plurality of frames andthe determined second plurality of frames; and appending the created setof snippets together into an online preview.
 2. The method of claim 1,further comprising: presenting the preview to the user, wherein thepresented preview is generated from a plurality of media resources. 3.The method of claim 1, further comprising: in response to a request by auser to view a preview associated with a media file, presenting thepreview to the user, wherein the preview is generated from appending aset of snippets comprising a collected plurality of frames that areassociated with the requested media file.
 4. The method of claim 2,wherein the received search string is inputted via a graphical userinterface.
 5. The method of claim 1, wherein the received plurality ofsocial comments is stored and tagged to correlate to the stored steamingmedia file and corresponding frame marker within the plurality of framemarkers.
 6. The method of claim 1, wherein the media file comprises atleast one of a plurality of movies, a plurality of videos, a pluralityof films, a plurality of television shows, a plurality of network shows,and a plurality of cable shows.
 7. The method of claim 1, wherein theanalyzing comprises the use of a plurality of semantic analysistechniques.
 8. The method of claim 1, wherein the received plurality ofsocial comments is entered by using a secondary device connected to aservice streaming the media file or through a pause menu on a viewingdevice streaming the media file.
 9. The method of claim 1, wherein thedetermined first plurality of frames are associated with at least onepositive sentiment within the determined plurality of positivesentiments.
 10. A computer system for generating a preview associatedwith a media file, the computer system comprising: one or moreprocessors, one or more computer-readable memories, one or morecomputer-readable tangible storage devices, and program instructionsstored on at least one of the one or more storage devices for executionby at least one of the one or more processors via at least one of theone or more memories, wherein the computer system is capable ofperforming a method comprising: receiving a plurality of social commentsassociated with a plurality of frames corresponding to the media file,wherein the received plurality of social comments comprises collecting aplurality of input from a plurality of different users, wherein theplurality of input is obtained live via an internet, a graphical userinterface, an online communication system, or a use of social media viaa secondary device connected to a service streaming the media file;storing the streaming media file in a first repository with a pluralityof frame markers corresponding to the stored streaming media file;storing the received plurality of social comments in a secondrepository, analyzing the stored plurality of social comments;annotating each social comment within the analyzed plurality of socialcomments with at least one sentiment and at least one keyword in themedia file; classifying the analyzed annotated plurality of socialcomments according to the at least one sentiment and the at least onekeyword in the media file, wherein classifying the annotated pluralityof social comments comprises determining a plurality of positivesentiments about a plurality of frames associated with the media file;receiving a search string regarding a media file preference, wherein thesearch string is inputted online by a user; in response to receiving thesearch string regarding the media file preference, determining from thefirst repository and the second repository a first plurality of framesthat match a criteria associated with the received search string;determining a second plurality of frames that include a set of framesdirectly before and a set of frames directly after the determined firstplurality of frames that match the criteria associated with the searchstring; creating a set of snippets based on the determined firstplurality of frames and the determined second plurality of frames; andappending the created set of snippets together into an online preview.11. The computer system of claim 10, further comprising: presenting thepreview to the user, wherein the presented preview is generated from aplurality of media resources.
 12. The computer system of claim 10,further comprising: in response to a request by a user to view a previewassociated with a media file, presenting the preview to the user,wherein the preview is generated from appending a set of snippetscomprising a collected plurality of frames that are associated with therequested media file.
 13. The computer system of claim 11, wherein thereceived search string is inputted via a graphical user interface. 14.The computer system of claim 10, wherein the received plurality ofsocial comments is stored and tagged to correlate to the stored steamingmedia file and corresponding frame marker within the plurality of framemarkers.
 15. The computer system of claim 10, wherein the media filecomprises at least one of a plurality of movies, a plurality of videos,a plurality of films, a plurality of television shows, a plurality ofnetwork shows, and a plurality of cable shows.
 16. The computer systemof claim 10, wherein the analyzing comprises the use of a plurality ofsemantic analysis techniques.
 17. The computer system of claim 10,wherein the received plurality of social comments is entered by using asecondary device connected to a service streaming the media file orthrough a pause menu on a viewing device streaming the media file. 18.The computer system of claim 10, wherein the determined first pluralityof frames are associated with at least one positive sentiment within thedetermined plurality of positive sentiments.
 19. A computer programproduct for generating a preview associated with a media file, thecomputer program product comprising: one or more computer-readablestorage devices and program instructions stored on at least one of theone or more tangible storage devices, the program instructionsexecutable by a processor, the program instructions comprising: programinstructions to receive a plurality of social comments associated with aplurality of frames corresponding to the media file, wherein thereceived plurality of social comments comprises collecting a pluralityof input from a plurality of different users, wherein the plurality ofinput is obtained live via an internet, a graphical user interface, anonline communication system, or a use of social media via a secondarydevice connected to a service streaming the media file; programinstructions to store the streaming media file in a first repositorywith a plurality of frame markers corresponding to the stored streamingmedia file; program instructions to store the received plurality ofsocial comments in a second repository, program instructions to analyzethe stored plurality of social comments; program instructions toannotate each social comment within the analyzed plurality of socialcomments with at least one sentiment and at least one keyword in themedia file; program instructions to classify the analyzed annotatedplurality of social comments according to the at least one sentiment andthe at least one keyword in the media file, wherein classifying theannotated plurality of social comments comprises determining a pluralityof positive sentiments about a plurality of frames associated with themedia file; program instructions to receive a search string regarding amedia file preference, wherein the search string is inputted online by auser; in response to receiving the search string regarding the mediafile preference, program instructions to determine from the firstrepository and the second repository a first plurality of frames thatmatch a criteria associated with the received search string; programinstructions to determine a second plurality of frames that include aset of frames directly before and a set of frames directly after thedetermined first plurality of frames that match the criteria associatedwith the search string; program instructions to create a set of snippetsbased on the determined first plurality of frames and the determinedsecond plurality of frames; and program instructions to append thecreated set of snippets together into an online preview.
 20. Thecomputer program product of claim 19, further comprising: programinstructions to present the preview to the user, wherein the presentedpreview is generated from a plurality of media resources.